Yingying X Wang

US Patent:

20210378106, Dec 2, 2021

Filed:

May 28, 2021

Appl. No.:

17/333570

Inventors:

- Mountain View CA, US
Christopher Malone - Mountain View CA, US
Melanie Beauchemin - Mountain View CA, US
Padam Jain - San Jose CA, US
Teckgyu Kang - Saratoga CA, US
Yuan Li - Sunnyvale CA, US
Connor Burgess - Alameda CA, US
Norman Paul Jouppi - Palo Alto CA, US
Yingying Wang - Sunnyvale CA, US

International Classification:

H05K 3/34
H05K 7/20
H01L 23/00

Abstract:

A method of manufacturing a chip assembly comprises joining an in-process unit to a printed circuit board; reflowing a bonding material disposed between and electrically connecting the in-process unit with the printed circuit board, the bonding material having a first reflow temperature; and then joining a heat distribution device to the plurality of semiconductor chips using a thermal interface material (“TIM”) having a second reflow temperature that is lower than the first reflow temperature. The in-process unit further comprises a substrate having an active surface, a passive surface, and contacts exposed at the active surface; an interposer electrically connected to the substrate; a plurality of semiconductor chips overlying the substrate and electrically connected to the substrate through the interposer, and a stiffener overlying the substrate and having an aperture extending therethrough, the plurality of semiconductor chips being positioned within the aperture.

US Patent:

20210225077, Jul 22, 2021

Filed:

Apr 5, 2021

Appl. No.:

17/222176

Inventors:

- Santa Monica CA, US
Zhou Ren - Bellevue WA, US
Yuncheng LI - Los Angeles CA, US
Zehao Xue - Los Angeles CA, US
Yingying Wang - Marina del Rey CA, US

International Classification:

G06T 17/20
G06T 7/73
G06N 3/08
G06N 3/04

Abstract:

Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing a program and a method for receiving a monocular image that includes a depiction of a hand and extracting features of the monocular image using a plurality of machine learning techniques. The program and method further include modeling, based on the extracted features, a pose of the hand depicted in the monocular image by adjusting skeletal joint positions of a three-dimensional (3D) hand mesh using a trained graph convolutional neural network (CNN); modeling, based on the extracted features, a shape of the hand in the monocular image by adjusting blend shape values of the 3D hand mesh representing surface features of the hand depicted in the monocular image using the trained graph CNN; and generating, for display, the 3D hand mesh adjusted to model the pose and shape of the hand depicted in the monocular image.

US Patent:

20200402305, Dec 24, 2020

Filed:

Sep 2, 2020

Appl. No.:

17/010256

Inventors:

- Santa Monica CA, US
Zhou Ren - Bellevue WA, US
Yuncheng Li - Los Angeles CA, US
Zehao Xue - Los Angeles CA, US
Yingying Wang - Marina del Rey CA, US

International Classification:

G06T 17/20
G06T 7/73
G06N 3/08
G06N 3/04

Abstract:

Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing a program and a method for receiving a monocular image that includes a depiction of a hand and extracting features of the monocular image using a plurality of machine learning techniques. The program and method further include modeling, based on the extracted features, a pose of the hand depicted in the monocular image by adjusting skeletal joint positions of a three-dimensional (3D) hand mesh using a trained graph convolutional neural network (CNN); modeling, based on the extracted features, a shape of the hand in the monocular image by adjusting blend shape values of the 3D hand mesh representing surface features of the hand depicted in the monocular image using the trained graph CNN; and generating, for display, the 3D hand mesh adjusted to model the pose and shape of the hand depicted in the monocular image.

US Patent:

20170091976, Mar 30, 2017

Filed:

Sep 29, 2015

Appl. No.:

14/869514

Inventors:

- Burbank CA, US
Kerstin RUHLAND - Dublin, IE
Michael NEFF - Oakland CA, US
Yingying WANG - Davis CA, US

International Classification:

G06T 13/40
G06F 3/01

Abstract:

Techniques for rendering realistic depictions of conversational gestures are provided. Embodiments include generating a data model for a first conversational gesture type, by analyzing captured video data to determine motion attribute data for a plurality of conversational gestures. Additionally, upon receiving a request to splice a gesture of the first conversational gesture type into a first animation, embodiments determine a locomotion of a first virtual character, while the first virtual character is interacting with a second virtual character within the first animation. A gesture of the first conversational gesture type is then stylized, using the generated data model and based on the determined locomotion of the first virtual character within the animation. Embodiments splice the stylized gesture into the locomotion of the first virtual character within the received animation data.